期刊文献+

基于短路阻抗及ΔU-I_(1)轨迹特征联合分析的变压器绕组变形故障在线检测方法 被引量:11

Online detection method of transformer winding deformation based on combined analysis of short circuit impedance andΔUI_(1) locus characteristics
下载PDF
导出
摘要 为解决短路阻抗法不能进行故障类型识别及其与ΔU-I_(1)轨迹法均易受设备测量误差干扰的问题,提出了基于短路电抗及ΔU-I_(1)轨迹特征联合分析的绕组变形在线检测方法。介绍了在线短路阻抗法的原理,并根据互感器测量误差的短时不变性提出了减小测量误差的计算方法。介绍了ΔU-I_(1)轨迹法的原理,然后给出基于短路阻抗及ΔU-I_(1)轨迹特征联合分析的变压器绕组变形在线检测步骤和判据。通过建立变压器的仿真模型,对所提方法的有效性及考虑测量误差时的准确性进行了验证。结果表明,所提方法能在考虑测量误差时准确识别变压器的绕组变形故障,具有工频带电监测和故障类型识别的优点,提高了绕组变形故障识别的精度。 In order to solve the problem that the short circuit impedance method cannot identify fault types and that both the short circuit impedance method and theΔUI_(1)locus method are susceptible to the interference of equipment measurement errors,an online winding deformation detection method based on the combined analysis of short circuit impedance andΔUI_(1)locus characteristics is proposed.The principle of online short circuit impedance method is introduced,and a calculation method of short circuit impedance based on the short time invariance of measurement error is put forward to reduce the measurement error.The principle ofΔUI_(1)locus method is introduced,then the online detection steps and criteria of transformer winding deformation based on combined analysis of short circuit impedance andΔUI_(1)locus characteristics are given.The effectiveness of the proposed method and its accuracy considering measuring errors are verified by establishing a transformer simulation model.The results show that the proposed method can accurately identify transformer winding deformation faults when considering measurement error,and has the advantages of live detection and fault type identification,which improves the identification accuracy of winding deformation fault.
作者 李振华 蒋伟辉 喻彩云 陈兴新 李振兴 徐艳春 LI Zhenhua;JIANG Weihui;YU Caiyun;CHEN Xingxin;LI Zhenxing;XU Yanchun(College of Electrical Engineering&New Energy,China Three Gorges University,Yichang 443002,China;Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station,China Three Gorges University,Yichang 443002,China)
出处 《电力自动化设备》 EI CSCD 北大核心 2021年第7期203-209,217,共8页 Electric Power Automation Equipment
基金 国家自然科学基金资助项目(51507091) 三峡大学学位论文培优基金资助项目(2020SSPY052)。
关键词 电力变压器 绕组变形 短路阻抗 ΔU-I1轨迹 在线检测 power transformers winding deformation short circuit impedance ΔUI_(1)locus online detection
  • 相关文献

参考文献13

二级参考文献127

共引文献273

同被引文献120

引证文献11

二级引证文献31

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部